Consensus for experimental design in electromyography (CEDE) project: single motor unit matrix

Eduardo Martinez-Valdes, Roger M Enoka, Aleš Holobar, Kevin McGill, Dario Farina, Manuela Besomi, François Hug, Deborah Falla, Richard G Carson, Edward A Clancy, Catherine Disselhorst-Klug, Jaap H van Dieën, Kylie Tucker, Simon Gandevia, Madeleine Lowery, Karen Søgaard, Thor Besier, Roberto Merletti, Matthew C Kiernan, John C RothwellEric Perreault, Paul W Hodges*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Original languageEnglish
Article number102726
Number of pages14
JournalJournal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Volume68
Early online date28 Nov 2022
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Copyright © 2022 Elsevier Ltd. All rights reserved.

Keywords

  • Motor unit
  • Motor neuron
  • High-density surface electromyography
  • Intramuscular electromyography

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